High-level synthesis scheduling and allocation using genetic algorithms

Abstract

In this article a scheduling method is presented which is capable of allocating supplementary resources during scheduling. This makes it very suitable in synthesis strategies based on lower bound estimations techniques. The method is based on genetic algorithms. Special coding techniques and analysis methods are used to improve the runtime and quality of the results. The scheduler can easily be extended to cover other architectural issues and (for example) provides ways to make trade-offs between functional unit allocation and register allocation. Experiments and comparisons show high quality results and fast run times that outperform results produced by other heuristic scheduling methods.